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20 hours ago •
satijalab
satijalab
Problem with Leverage Score Calculation for Integration of Single Cell Seurat Objects
I am trying to use the SketchData function with the Leverage Score method, and the computation will not go through. All of my Seurat objects seem consistent with each other, and the matrices don't seem to have any major issues. Since everything seems okay, it perplexes me why I am having this issue.
This is the code that I am currently running (the error occurs on the last line):
### This script takes as input the Seurat Objects from each CODEX sample in the atlas and creates a combined CODEX Atlas Object
library(Seurat)
options(Seurat.object.assay.version = 'v5')
library(tidyverse)
library(patchwork)
library(readr)
library(dplyr)
library(ggrepel)
library(ggplot2)
library(RColorBrewer)
options(future.globals.maxSize = 1e9)
options(Seurat.object.assay.version = "v5")
source("/mnt/isilon/some_lab/myname/CODEX_Functions.R")
#Import RDS Files
#load in every individual R file for each sample
Sample1 <- readRDS("/mnt/isilon/some_lab/myname/Sample1.RDS")
Sample2 <- readRDS("/mnt/isilon/some_lab/myname/Sample2.RDS")
#Work with Combined Data
ob.list <- c()
ob.list[[1]] <- Sample1
ob.list[[2]] <- Sample2
combined <- merge(x = ob.list[[1]], y = c(ob.list[[2]]), add.cell.ids = c("Sample1", "Sample2"))
combined <- JoinLayers(combined)
#important_features <- c("AB", "CD", "EF", "GH", "IJ", "KL", "MN", "OP", "QR", "ST", "UV", "WX")
important_features = rownames(combined)
VariableFeatures(combined) = important_features
combined <- NormalizeData(object = combined, normalization.method = "CLR", margin = 1)
combined <- split(combined, f = combined$orig.ident)
combined <- SketchData(object = combined, ncells = 50000, method = "LeverageScore", sketched.assay = "sketch")
The error that I am getting is the following:
Calcuating Leverage Score
Running LeverageScore for layer data.pHGG_Autopsy
sampling 5000 cells
Performing QR decomposition
'as(<dgeMatrix>, "dgCMatrix")' is deprecated.
Use 'as(., "CsparseMatrix")' instead.
See help("Deprecated") and help("Matrix-deprecated").
Error in backsolve(r = R, x = diag(x = ncol(x = R))) :
singular matrix in 'backsolve'. First zero in diagonal [52]
This is the SessionInfo():
R version 4.2.3 (2023-03-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux 9.1 (Plow)
Matrix products: default
BLAS: /cm/shared/apps_chop/R/4.2.3/lib64/R/lib/libRblas.so
LAPACK: /cm/shared/apps_chop/R/4.2.3/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] RColorBrewer_1.1-3 ggrepel_0.9.3 patchwork_1.1.2 lubridate_1.9.2
[5] forcats_1.0.0 stringr_1.5.0 dplyr_1.1.2 purrr_1.0.1
[9] readr_2.1.4 tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.2
[13] tidyverse_2.0.0 Seurat_4.9.9.9049 SeuratObject_4.9.9.9086 sp_2.0-0
loaded via a namespace (and not attached):
[1] Rtsne_0.16 colorspace_2.1-0 deldir_1.0-9 ellipsis_0.3.2
[5] ggridges_0.5.4 RcppHNSW_0.4.1 rstudioapi_0.14 spatstat.data_3.0-1
[9] leiden_0.4.3 listenv_0.9.0 RSpectra_0.16-1 fansi_1.0.4
[13] codetools_0.2-19 splines_4.2.3 polyclip_1.10-4 spam_2.9-1
[17] jsonlite_1.8.5 ica_1.0-3 cluster_2.1.4 png_0.1-8
[21] uwot_0.1.16 shiny_1.7.4 sctransform_0.3.5 spatstat.sparse_3.0-2
[25] BiocManager_1.30.21 compiler_4.2.3 httr_1.4.6 Matrix_1.5-4
[29] fastmap_1.1.1 lazyeval_0.2.2 cli_3.6.1 later_1.3.1
[33] htmltools_0.5.5 tools_4.2.3 igraph_1.5.0 dotCall64_1.0-2
[37] gtable_0.3.3 glue_1.6.2 RANN_2.6.1 reshape2_1.4.4
[41] Rcpp_1.0.10 scattermore_1.2 vctrs_0.6.3 spatstat.explore_3.2-1
[45] nlme_3.1-162 progressr_0.13.0 lmtest_0.9-40 spatstat.random_3.1-5
[49] globals_0.16.2 timechange_0.2.0 mime_0.12 miniUI_0.1.1.1
[53] lifecycle_1.0.3 irlba_2.3.5.1 renv_0.17.3 goftest_1.2-3
[57] future_1.32.0 MASS_7.3-60 zoo_1.8-12 scales_1.2.1
[61] hms_1.1.3 promises_1.2.0.1 spatstat.utils_3.0-3 parallel_4.2.3
[65] reticulate_1.30 pbapply_1.7-2 gridExtra_2.3 stringi_1.7.12
[69] fastDummies_1.6.3 rlang_1.1.1 pkgconfig_2.0.3 matrixStats_1.0.0
[73] lattice_0.21-8 ROCR_1.0-11 tensor_1.5 htmlwidgets_1.6.2
[77] cowplot_1.1.1 tidyselect_1.2.0 parallelly_1.36.0 RcppAnnoy_0.0.20
[81] plyr_1.8.8 magrittr_2.0.3 R6_2.5.1 generics_0.1.3
[85] pillar_1.9.0 withr_2.5.0 fitdistrplus_1.1-11 survival_3.5-5
[89] abind_1.4-5 future.apply_1.11.0 KernSmooth_2.23-21 utf8_1.2.3
[93] spatstat.geom_3.2-1 plotly_4.10.2 tzdb_0.4.0 grid_4.2.3
[97] data.table_1.14.8 digest_0.6.32 xtable_1.8-4 httpuv_1.6.11
[101] munsell_0.5.0 viridisLite_0.4.2
Hello. I am also experiencing this type of issue. I have a dataset with 30 layers, 3 of which have fewer than 10 K cells and several others that have 10-12 K cells. One of the layers with fewer than 10 K cells returns this same error message. I have resorted to editing the SketchData function to not calculate leverage scores on any layers with fewer than 10 K cells by subsetting the object, as I do not know how to edit the LeverageScore function to return values of 1 if the matrix following QR decomposition is singular. It would be awesome if you guys could edit the function to do so.
Hello. I'm also experiencing this error. My data has 174 layers.
Any suggestions?
I am trying to use the SketchData function with the Leverage Score method, and the computation will not go through. All of my Seurat objects seem consistent with each other, and the matrices don't seem to have any major issues. Since everything seems okay, it perplexes me why I am having this issue.
This is the code that I am currently running (the error occurs on the last line):
### This script takes as input the Seurat Objects from each CODEX sample in the atlas and creates a combined CODEX Atlas Object library(Seurat) options(Seurat.object.assay.version = 'v5') library(tidyverse) library(patchwork) library(readr) library(dplyr) library(ggrepel) library(ggplot2) library(RColorBrewer) options(future.globals.maxSize = 1e9) options(Seurat.object.assay.version = "v5") source("/mnt/isilon/some_lab/myname/CODEX_Functions.R") #Import RDS Files #load in every individual R file for each sample Sample1 <- readRDS("/mnt/isilon/some_lab/myname/Sample1.RDS") Sample2 <- readRDS("/mnt/isilon/some_lab/myname/Sample2.RDS") #Work with Combined Data ob.list <- c() ob.list[[1]] <- Sample1 ob.list[[2]] <- Sample2 combined <- merge(x = ob.list[[1]], y = c(ob.list[[2]]), add.cell.ids = c("Sample1", "Sample2")) combined <- JoinLayers(combined) #important_features <- c("AB", "CD", "EF", "GH", "IJ", "KL", "MN", "OP", "QR", "ST", "UV", "WX") important_features = rownames(combined) VariableFeatures(combined) = important_features combined <- NormalizeData(object = combined, normalization.method = "CLR", margin = 1) combined <- split(combined, f = combined$orig.ident) combined <- SketchData(object = combined, ncells = 50000, method = "LeverageScore", sketched.assay = "sketch")The error that I am getting is the following:
Calcuating Leverage Score Running LeverageScore for layer data.pHGG_Autopsy sampling 5000 cells Performing QR decomposition 'as(<dgeMatrix>, "dgCMatrix")' is deprecated. Use 'as(., "CsparseMatrix")' instead. See help("Deprecated") and help("Matrix-deprecated"). Error in backsolve(r = R, x = diag(x = ncol(x = R))) : singular matrix in 'backsolve'. First zero in diagonal [52]This is the SessionInfo():
R version 4.2.3 (2023-03-15) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux 9.1 (Plow) Matrix products: default BLAS: /cm/shared/apps_chop/R/4.2.3/lib64/R/lib/libRblas.so LAPACK: /cm/shared/apps_chop/R/4.2.3/lib64/R/lib/libRlapack.so locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 [4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C [10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices datasets utils methods base other attached packages: [1] RColorBrewer_1.1-3 ggrepel_0.9.3 patchwork_1.1.2 lubridate_1.9.2 [5] forcats_1.0.0 stringr_1.5.0 dplyr_1.1.2 purrr_1.0.1 [9] readr_2.1.4 tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.2 [13] tidyverse_2.0.0 Seurat_4.9.9.9049 SeuratObject_4.9.9.9086 sp_2.0-0 loaded via a namespace (and not attached): [1] Rtsne_0.16 colorspace_2.1-0 deldir_1.0-9 ellipsis_0.3.2 [5] ggridges_0.5.4 RcppHNSW_0.4.1 rstudioapi_0.14 spatstat.data_3.0-1 [9] leiden_0.4.3 listenv_0.9.0 RSpectra_0.16-1 fansi_1.0.4 [13] codetools_0.2-19 splines_4.2.3 polyclip_1.10-4 spam_2.9-1 [17] jsonlite_1.8.5 ica_1.0-3 cluster_2.1.4 png_0.1-8 [21] uwot_0.1.16 shiny_1.7.4 sctransform_0.3.5 spatstat.sparse_3.0-2 [25] BiocManager_1.30.21 compiler_4.2.3 httr_1.4.6 Matrix_1.5-4 [29] fastmap_1.1.1 lazyeval_0.2.2 cli_3.6.1 later_1.3.1 [33] htmltools_0.5.5 tools_4.2.3 igraph_1.5.0 dotCall64_1.0-2 [37] gtable_0.3.3 glue_1.6.2 RANN_2.6.1 reshape2_1.4.4 [41] Rcpp_1.0.10 scattermore_1.2 vctrs_0.6.3 spatstat.explore_3.2-1 [45] nlme_3.1-162 progressr_0.13.0 lmtest_0.9-40 spatstat.random_3.1-5 [49] globals_0.16.2 timechange_0.2.0 mime_0.12 miniUI_0.1.1.1 [53] lifecycle_1.0.3 irlba_2.3.5.1 renv_0.17.3 goftest_1.2-3 [57] future_1.32.0 MASS_7.3-60 zoo_1.8-12 scales_1.2.1 [61] hms_1.1.3 promises_1.2.0.1 spatstat.utils_3.0-3 parallel_4.2.3 [65] reticulate_1.30 pbapply_1.7-2 gridExtra_2.3 stringi_1.7.12 [69] fastDummies_1.6.3 rlang_1.1.1 pkgconfig_2.0.3 matrixStats_1.0.0 [73] lattice_0.21-8 ROCR_1.0-11 tensor_1.5 htmlwidgets_1.6.2 [77] cowplot_1.1.1 tidyselect_1.2.0 parallelly_1.36.0 RcppAnnoy_0.0.20 [81] plyr_1.8.8 magrittr_2.0.3 R6_2.5.1 generics_0.1.3 [85] pillar_1.9.0 withr_2.5.0 fitdistrplus_1.1-11 survival_3.5-5 [89] abind_1.4-5 future.apply_1.11.0 KernSmooth_2.23-21 utf8_1.2.3 [93] spatstat.geom_3.2-1 plotly_4.10.2 tzdb_0.4.0 grid_4.2.3 [97] data.table_1.14.8 digest_0.6.32 xtable_1.8-4 httpuv_1.6.11 [101] munsell_0.5.0 viridisLite_0.4.2
hi,you need run FindVariableFeatures(),after finsh, you can run sktchdata
